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  homepage: https://vlar-group.github.io/PhysInOne.html
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  ---
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- # PhysInOne: Visual Physics Learning and Reasoning in One Suite
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-
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- <p align="center">
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- <a href="https://vlar-group.github.io/PhysInOne.html">Project Page</a> |
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- <a href="https://arxiv.org/abs/2604.09415">Paper</a> |
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- <a href="TODO">Code</a> |
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- <a href="TODO">Dataset</a> |
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- <a href="TODO">Leaderboard</a>
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  </p>
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- ## Dataset Card
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-
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- ### Title, Authors, and Conference Information
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-
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- **Title:** PhysInOne: Visual Physics Learning and Reasoning in One Suite
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-
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- **Authors:** Siyuan Zhou, Hejun Wang, Hu Cheng, Jinxi Li, Dongsheng Wang, Junwei Jiang, Yixiao Jin, Jiayue Huang, Shiwei Mao, Shangjia Liu, Yafei Yang, Hongkang Song, Shenxing Wei, Zihui Zhang, Bing Wang, Zhihua Wang, Chuhang Zou, Bo Yang, and DataTeam.
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- **Affiliations:** vLAR Group, The Hong Kong Polytechnic University, Syai Singapore, Meta.
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- **Conference / Venue:** TODO.
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-
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- **Paper:** https://arxiv.org/abs/2604.09415
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-
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- **Project Page:** https://vlar-group.github.io/PhysInOne.html
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-
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  ### Summary
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  **PhysInOne** is a large-scale synthetic dataset for visual physics learning and reasoning. It contains **153,810 dynamic 3D scenes** and **2 million annotated videos**, covering **71 basic physical phenomena** across four domains of everyday physics: **mechanics**, **optics**, **fluid dynamics**, and **magnetism**.
 
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  homepage: https://vlar-group.github.io/PhysInOne.html
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  ---
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+ <h1 align="center">PhysInOne: Visual Physics Learning and Reasoning in One Suite</h1>
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+
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+ <p align="center">
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+ Siyuan Zhou<sup>1†</sup>
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+ Hejun Wang<sup>1†</sup>
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+ Hu Cheng<sup>1†</sup>
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+ Jinxi Li<sup>1†</sup>
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+ Dongsheng Wang<sup>1†</sup>
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+ Junwei Jiang<sup>1†</sup> <br>
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+ Yixiao Jin<sup>1†</sup>
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+ Jiayue Huang<sup>1†</sup>
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+ Shiwei Mao<sup>1†</sup>
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+ Shangjia Liu<sup>2</sup>
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+ Yafei Yang<sup>1</sup> <br>
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+ Hongkang Song<sup>1</sup>
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+ Shenxing Wei<sup>1</sup>
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+ Zihui Zhang<sup>1</sup>
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+ DataTeam<sup>1*</sup>
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+ Bing Wang<sup>2</sup>
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+ Zhihua Wang<sup>3</sup>
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+ Chuhang Zou<sup>4</sup>
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+ Bo Yang<sup>1‡</sup>
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+ </p>
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+
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+ <p align="center">
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+ <sup>1</sup> vLAR Group
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+ <sup>2</sup> The Hong Kong Polytechnic University
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+ <sup>3</sup> Syai Singapore
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+ <sup>4</sup> Meta
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+ </p>
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+
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+ <p align="center">
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+ <sup>†</sup> Equal Contribution
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+ <sup>‡</sup> Corresponding Author
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+ <sup>*</sup> Data Team
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+ </p>
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+
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+ <p align="center">
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+ <strong>CVPR 2026</strong>
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+ </p>
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+
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+ <p align="center">
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+ <a href="https://vlar-group.github.io/PhysInOne.html">
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+ <img src="https://img.shields.io/badge/Project-Page-purple">
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+ </a>
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+ <a href="https://arxiv.org/abs/2604.09415">
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+ <img src="https://img.shields.io/badge/Paper-ArXiv-red">
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+ </a>
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+ <a href="TODO">
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+ <img src="https://img.shields.io/badge/Code-GitHub-black">
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+ </a>
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+ <a href="TODO">
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+ <img src="https://img.shields.io/badge/Dataset-HuggingFace-yellow">
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+ </a>
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+ <a href="TODO">
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+ <img src="https://img.shields.io/badge/Leaderboard-Coming_Soon-blue">
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+ </a>
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  </p>
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  ### Summary
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  **PhysInOne** is a large-scale synthetic dataset for visual physics learning and reasoning. It contains **153,810 dynamic 3D scenes** and **2 million annotated videos**, covering **71 basic physical phenomena** across four domains of everyday physics: **mechanics**, **optics**, **fluid dynamics**, and **magnetism**.